Monthly‐, medium‐, and short‐range flood warning: testing the limits of predictability

This paper describes a case study that explores the limits of the predictability of floods, by combining forecasts with multiple spatial and temporal resolutions. Monthly, medium- and short range numerical weather prediction (NWP) data are input to the European Flood Alert System for a flood event that affected rivers in Romania in October 2007. The NWP data comprise ensembles and deterministic forecasts of different spatial resolutions and lead times from different weather prediction models. Results are explored in terms of the individual NWP components as well as the ensemble. In this case study, ensembles of monthly weather forecasts contribute only marginally to the early warning, although some indication is given as early as 3 weeks before the event. The 15-day medium-range weather forecasts produce early flood warning information 9 to 11 days in advance. As the event draws nearer and is in range to be captured by the higher resolution ensemble forecasts, the spatial extent of the event is forecast with much more precision than with the medium-range. A novel post-processing method for the calculation of river discharge is applied to those stations where observations are available, and is able to correct for time-shifts and to improve the quantitative forecast. The study illustrates how a combination of forecasts and post-processing improves the lead time for early flood warnings by 2 to 3 days, while remaining reliable also in the short-range. Copyright © 2009 Royal Meteorological Society

[1]  Hannah L. Cloke,et al.  Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures , 2008 .

[2]  K. Beven,et al.  Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS) , 2005 .

[3]  A. Montani,et al.  A spatial verification method applied to the evaluation of high‐resolution ensemble forecasts , 2008 .

[4]  Renate Hagedorn,et al.  Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part II: Precipitation , 2008 .

[5]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[6]  K. Bogner,et al.  Error‐correction methods and evaluation of an ensemble based hydrological forecasting system for the Upper Danube catchment , 2008 .

[7]  De Roo Arie,et al.  Eurorisk/Preview Report on the Technical Quality, Functional Quality and Forecast Value of Meteorological and Hydrological Forecasts , 2007 .

[8]  J. Thielen,et al.  The European Flood Alert System – Part 1: Concept and development , 2008 .

[9]  E. Roulin,et al.  Skill and relative economic value of medium-range hydrological ensemble predictions , 2006 .

[10]  G. Lindström,et al.  Evaluation and calibration of operational hydrological ensemble forecasts in Sweden , 2008 .

[11]  Breanndán Ó Nualláin,et al.  Parameter optimisation and uncertainty assessment for large-scale streamflow simulation with the LISFLOOD model , 2007 .

[12]  Florian Pappenberger,et al.  Hydrological aspects of meteorological verification , 2008 .

[13]  Roberto Buizza,et al.  A strategy for high‐resolution ensemble prediction. II: Limited‐area experiments in four Alpine flood events , 2001 .

[14]  R. Buizza,et al.  Flood forecasting using medium-range probabilistic weather prediction , 2005 .

[15]  R. Buizza,et al.  The Hydrologic Ensemble Prediction EXperiment (HEPEX) , 2006 .

[16]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[17]  Jutta Thielen,et al.  EFAS forecasts for the March–April 2006 flood in the Czech part of the Elbe River Basin—a case study , 2008 .

[18]  S. Vogt,et al.  MAP D‐PHASE: real‐time demonstration of hydrological ensemble prediction systems , 2008 .

[19]  Todini,et al.  Coupling meteorological and hydrological models for flood forecasting , 2005 .

[20]  Bruno Torrésani,et al.  Practical Time-Frequency Analysis, Volume 9: Gabor and Wavelet Transforms, with an Implementation in S , 1998 .

[21]  Jutta Thielen,et al.  Ensemble predictions and perceptions of risk, uncertainty, and error in flood forecasting , 2007 .

[22]  Keith Beven,et al.  Uncertainty analysis of the rainfall runoff model LisFlood within the Generalized Likelihood Uncertainty Estimation (GLUE) , 2004 .

[23]  G. Thirel,et al.  On the Impact of Short-Range Meteorological Forecasts for Ensemble Streamflow Predictions , 2008 .

[24]  Mats Hamrud,et al.  The new ECMWF VAREPS (Variable Resolution Ensemble Prediction System) , 2007 .

[25]  F. Molteni,et al.  The ECMWF Ensemble Prediction System: Methodology and validation , 1996 .

[26]  Florian Pappenberger,et al.  The Skill of ECMWF Precipitation and Temperature Predictions in the Danube Basin as Forcings of Hydrological Models , 2009 .

[27]  Jutta Thielen,et al.  The european flood alert system EFAS - Part 2: statistical skill assessment of probabilistic and deterministic operational forecasts. , 2008 .

[28]  A. Hollingsworth,et al.  Probabilistic Predictions of Precipitation Using the ECMWF Ensemble Prediction System , 1999 .

[29]  J. Knijff.  LISFLOOD Distributed Water Balance and Flood Simulation Model , 2008 .

[30]  David S. Stoffer,et al.  Time series analysis and its applications , 2000 .

[31]  J. M. Van Der Knijff,et al.  Please Scroll down for Article International Journal of Geographical Information Science Lisflood: a Gis-based Distributed Model for River Basin Scale Water Balance and Flood Simulation(2008)'lisflood: a Gis-based Distributed Model for River Basin Scale Water Balance and Flood Simulation',internatio , 2022 .

[32]  Patrick Matgen,et al.  Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[33]  Martyn P. Clark,et al.  The Hydrological Ensemble Prediction Experiment , 2007 .

[34]  Maria-Helena Ramos,et al.  Development of decision support products based on ensemble forecasts in the European flood alert system , 2007 .

[35]  J. McBride,et al.  Verification of Quantitative Precipitation Forecasts from Operational Numerical Weather Prediction Models over Australia , 2000 .

[36]  Martyn P. Clark,et al.  HEPEX: The Hydrological Ensemble Prediction Experiment , 2007 .

[37]  K. Beven,et al.  Parameter conditioning and prediction uncertainties of the LISFLOOD-WB distributed hydrological model , 2006 .

[38]  Jutta Thielen,et al.  Aims, challenges and progress of the Hydrological Ensemble Prediction Experiment (HEPEX) following the third HEPEX workshop held in Stresa 27 to 29 June 2007 , 2008 .

[39]  K. Beven,et al.  Development of a European flood forecasting system , 2003 .

[40]  F. Molteni,et al.  A strategy for high‐resolution ensemble prediction. I: Definition of representative members and global‐model experiments , 2001 .